Render MCP Server
Manage your Render resources from AI-powered apps like Cursor and Claude.
The Render MCP server is currently in early access.
Please submit bugs and feature requests on the server's public GitHub repository.
Use Render's official Model Context Protocol (MCP) server to manage your Render infrastructure directly from compatible AI apps, such as Cursor and Claude. With natural language prompts, you can spin up new services, query your databases, and more.
See some example prompts below.
How it works
Render hosts an instance of its MCP server at the following URL:
https://mcp.render.com/mcp
You can configure compatible AI apps (such as Cursor) to communicate with this server. When you provide a relevant prompt, your app intelligently calls the MCP server to execute supported platform actions:
In the example diagram above:
- A user prompts Cursor to "List my Render services".
- Cursor intelligently detects that the Render MCP server supports actions relevant to the prompt.
- Cursor directs the MCP server to execute the
list_services
"tool", which calls the Render API to fetch the corresponding data.
Alternatively, you can install the Render MCP server on your local machine. Both methods are covered in Setup.
To explore the implementation of the MCP server itself, see the open-source project:
Setup
1. Create an API key
The MCP server uses an API key to authenticate with the Render platform. Create an API key from your Account Settings page:
Render API keys are broadly scoped. They grant access to all workspaces and services your account can access.
Before proceeding, make sure you're comfortable granting these permissions to your AI app. The Render MCP server currently supports only one potentially destructive operation: modifying an existing service's environment variables.
2. Configure your AI app
Next, we'll configure your AI app to use the Render MCP server. Most compatible AI apps define their MCP configuration in a JSON file (such as ~/.cursor/mcp.json
for Cursor).
+ See configuration docs for popular apps
Select the tab below that corresponds to your MCP configuration method.
We strongly recommend using one of the Hosted configurations unless you specifically need to run the MCP server locally.
To use this configuration, your AI app must support communicating with MCP servers using streamable HTTP.
With this configuration, your AI app communicates directly with Render's hosted MCP server over HTTP.
Add JSON with the format below to your app's MCP configuration (substitute <YOUR_API_KEY>
with your API key):
{ "mcpServers": { "render": { "url": "https://mcp.render.com/mcp", "headers": { "Authorization": "Bearer <YOUR_API_KEY>" } } }}
The mcpServers
key above might differ for specific apps. For example, Zed uses context_servers
and GitHub Copilot uses servers
. Consult your app's documentation for details.
This configuration requires npm
.
With this configuration, your AI app spins up mcp-remote
as a local, stdio-based MCP server, which then proxies requests to Render's hosted MCP server over HTTP.
Add JSON with the format below to your app's MCP configuration (substitute <YOUR_API_KEY>
with your API key):
{ "mcpServers": { "render": { "command": "npx", "args": [ "mcp-remote", "https://mcp.render.com/mcp", "--header", "Authorization: Bearer ${AUTH_TOKEN}" ], "env": { "AUTH_TOKEN": "<YOUR_API_KEY>" } } }}
The mcpServers
key above might differ for specific apps. For example, Zed uses context_servers
and GitHub Copilot uses servers
. Consult your app's documentation for details.
This method requires docker
.
With this configuration, your AI app pulls and runs the Render MCP server as a Docker container.
Add JSON with the format below to your app's MCP configuration (substitute <YOUR_API_KEY>
with your API key):
{ "mcpServers": { "render": { "command": "docker", "args": [ "run", "-i", "--rm", "-e", "RENDER_API_KEY", "-v", "render-mcp-server-config:/config", "ghcr.io/render-oss/render-mcp-server" ], "env": { "RENDER_API_KEY": "<YOUR_API_KEY>" } } }}
The mcpServers
key above might differ for specific apps. For example, Zed uses context_servers
and GitHub Copilot uses servers
. Consult your app's documentation for details.
With this configuration, your AI app runs the Render MCP server executable directly.
-
Install the MCP server executable using one of the methods described in Local installation, then return here.
-
Add JSON with the format below to your app's MCP configuration (substitute your API key and the path to your MCP server executable):
json{"mcpServers": {"render": {"command": "/path/to/render-mcp-server-executable","env": {"RENDER_API_KEY": "<YOUR_API_KEY>"}}}}The
mcpServers
key above might differ for specific apps. For example, Zed usescontext_servers
and GitHub Copilot usesservers
. Consult your app's documentation for details.
You're ready to start prompting! Get started with some example prompts below.
Example usage
Your AI app can use the Render MCP server to perform a wide variety of platform actions. Here are some basic example prompts to get you started:
Service creation
Create a new database named user-db with 5 GB storage
Deploy an example Flask web service on Render using https://github.com/render-examples/flask-hello-world
Data analysis
Using my Render database, tell me which items were the most frequently bought together
Query my read replica for daily signup counts for the last 30 days
Troubleshooting
Pull the most recent error-level logs for my API service
Why isn't my site at example.onrender.com working?
Supported actions
The Render MCP server provides a "tool" for each platform action listed below (organized by resource type). Your AI app (the "MCP host") can combine these tools however it needs to perform the tasks you describe.
For more details on all available tools, see the project README.
Resource Type | Supported Actions |
---|---|
Workspaces |
|
Services |
|
Deploys |
|
Logs |
|
Render Postgres |
|
Render Key Value |
|
Local installation
Follow these instructions only if you're running the MCP server locally without Docker.
We strongly recommend instead using Render's hosted MCP server, because it automatically updates as new capabilities are added.
+ View installation methods
This method requires macOS or Linux.
-
Run the following
curl
command:shell$ curl -fsSL https://raw.githubusercontent.com/render-oss/render-mcp-server/refs/heads/main/bin/install.sh | sh -
Note the full path where the install script saved the downloaded executable. The output includes a message like the following:
✨ Successfully installed Render MCP Server to /Users/example/.local/bin/render-mcp-server
-
Open the MCP server's GitHub releases page.
-
Under the most recent release, download and unzip the executable that corresponds to your system's architecture.
- If a release asset isn't available for your architecture, select a different installation method.
-
Move the executable to the desired directory and note its full path.
Note for macOS users:
You might need to grant a system exception to run the downloaded executable, because it's from an "unknown developer." Learn more.
We recommend building from source only in the following cases:
- No other installation method works for your system.
- You're making custom changes to the MCP server.
-
Install the Go programming language if you haven't already.
-
Clone the MCP server repository and build the executable:
shell$ git clone https://github.com/render-oss/render-mcp-server.git$ cd render-mcp-server$ go buildThis creates a
render-mcp-server
executable in the repo's root directory. -
Note the full path to the newly built executable.
Limitations
The Render MCP server is currently in early access.
We will continue adding new capabilities over time. During the early access period, these updates might include breaking changes.
The Render MCP server attempts to minimize exposing sensitive information (like connection strings) to your AI app's context. However, Render does not guarantee that sensitive information will not be exposed. Exercise caution when interacting with secrets in your AI app.
Note the following additional limitations:
-
The MCP server supports creation of the following resources:
Other service types (private services, background workers, and cron jobs) are not yet supported.
-
The MCP server cannot create free instances.
-
The MCP server does not support all configuration options when creating services.
- For example, you cannot create image-backed services or set up IP allowlists. If there are options you'd like to see supported, please submit an issue on the MCP server's GitHub repository.
-
The MCP server does not support modifying or deleting existing Render resources, with one exception:
- You can modify an existing service's environment variables.
- To perform other modifications or deletions, use the Render Dashboard or REST API.
-
The MCP server does not support triggering deploys, modifying scaling settings, or other operational service controls.